In a world fueled by data, there is a significant demand from organizations to undertake the recollection and subsequent analysis of their preexisting data caches to generate forward-looking insights behind an enormous data collection. For example, by gathering and extracting decades of past meteorological weather patterns and data, we can discover meaningful trends that translate into solutions to help tackle climate change, optimize farming outputs and create sustainable electricity and water consumption habits. However, traditional methods of data storage inadvertently neglected the process of efficient retrieval, resulting in vast troves of potentially valuable data being lost and left to…

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